Triple
T8011835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Opel Grandland |
E186510
|
entity |
| Predicate | assembly |
P19323
|
FINISHED |
| Object | Eisenach, Germany |
E153084
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Eisenach, Germany | Statement: [Opel Grandland, assembly, Eisenach, Germany]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eisenach, Germany Context triple: [Opel Grandland, assembly, Eisenach, Germany]
-
A.
Saalfeld, Germany
Saalfeld is a historic town in the German state of Thuringia, known for its well-preserved medieval architecture and scenic location on the Saale River.
-
B.
Eisenach
chosen
Eisenach is a historic town in central Germany best known for its associations with Martin Luther and as the birthplace of composer Johann Sebastian Bach.
-
C.
Frohnhausen, Germany
Frohnhausen is a district in Germany known in part for its town-twinning partnership with Much Wenlock in England.
-
D.
Herzogenaurach, Germany
Herzogenaurach, Germany is a Bavarian town internationally known as the home base of major sportswear companies Adidas and Puma.
-
E.
Hesse, Germany
Hesse, Germany is a federal state in central Germany known for its financial hub Frankfurt am Main, forested landscapes, and historic cities such as Wiesbaden and Kassel.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca82abaffc8190ab8af79cdbc31ab3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3d722fbc8190b22745b581421f16 |
completed | March 31, 2026, 3:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc56acfcf88190a0e694f60f2907d2 |
completed | March 31, 2026, 11:20 p.m. |
Created at: March 30, 2026, 5:19 p.m.